Downtown Osaka Scene Text Dataset

  • Masakazu Iwamura
  • Takahiro Matsuda
  • Naoyuki Morimoto
  • Hitomi Sato
  • Yuki Ikeda
  • Koichi Kise
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9913)


This paper presents a new scene text dataset named Downtown Osaka Scene Text Dataset (in short, DOST dataset). The dataset consists of sequential images captured in shopping streets in downtown Osaka with an omnidirectional camera. Unlike most of existing datasets consisting of scene images intentionally captured, DOST dataset consists of uncontrolled scene images; use of an omnidirectional camera enabled us to capture videos (sequential images) of whole scenes surrounding the camera. Since the dataset preserved the real scenes containing texts as they were, in other words, they are scene texts in the wild. DOST dataset contained 32,147 manually ground truthed sequential images. They contained 935,601 text regions consisting of 797,919 legible and 137,682 illegible. The legible regions contained 2,808,340 characters. The dataset is evaluated using two existing scene text detection methods and one powerful commercial end-to-end scene text recognition method to know the difficulty and quality in comparison with existing datasets.


Scene text in the wild Uncontrolled scene text Omnidirectional camera Sequential image Video Japanese text 



The authors would like to thank the anonymous reviewers for their valuable comments and suggestions. This work is supported by JST CREST and JSPS KAKENHI #25240028.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Masakazu Iwamura
    • 1
  • Takahiro Matsuda
    • 1
  • Naoyuki Morimoto
    • 1
  • Hitomi Sato
    • 1
  • Yuki Ikeda
    • 1
  • Koichi Kise
    • 1
  1. 1.Department of Computer Science and Intelligent Systems, Graduate School of EngineeringOsaka Prefecture UniversitySakaiJapan

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